A new method for predicting patient survivorship using efficient Bayesian network learning

Cancer Informatics

Volumn 13, Issue , 2014, Pages 47-57

  Jiang, Xia ^a   Xue, Diyang ^a   Brufsky, Adam ^a   Khan, Seema ^b   Neapolitan, Richard ^b  

^a UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

^b NORTHWESTERN UNIVERSITY   (United States)

Author keywords

Bayesian network; Breast cancer; Cox proportional hazard model; Random survival forest; Survivorship prediction

Indexed keywords

ALGORITHM; ARTICLE; BAYESIAN LEARNING; BREAST CANCER; CANCER PATIENT; CANCER SURVIVAL; DECISION SUPPORT SYSTEM; HUMAN; PREDICTION; PROPORTIONAL HAZARDS MODEL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY ANALYSIS; VALIDATION PROCESS;

EID: 84896727645     PISSN: None     EISSN: 11769351     Source Type: Journal    
DOI: 10.4137/CIN.S13053     Document Type: Article

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